Unbiased stereology is used to quantify properties of a higher dimensional (e.g., 3D) object by viewing a lower dimensional (e.g., 2D) section of the object. Computer based stereology systems acquire data from 3D structures and have been primarily developed to extract an unbiased estimation of geometric properties including length, area, volume, and population size of objects within a biological sample. Biological applications of stereology include the unbiased estimation of a regional volume of tissue, surface area and length of cells and curvilinear fibers, and a total number of cells (objects of interest) in a defined reference space (region of interest).
Current computerized stereology systems enable mapping of anatomical regions by requiring a user to carry out several manual, non-automated steps when generating estimates of first- and second-order stereological parameters of biological microstructures.
For example, section or slice thickness determination is currently carried out by a user performing manual adjustments using the microscope's fine focusing mechanism to locate the boundaries of slice.
In addition, a user may also be required to manually locate and select objects of interest while stepping through stained tissue sections in order to perform quantitative analysis of biological microstructures.
For example, stereology often involves the application of assumption- and model-free (unbiased) geometric probes overlaid on stained tissue sections sampled in an unbiased systematic-random manner. Geometric probes for stereology studies include regional probes such as lines, points, spheres, and disectors placed at random with respect to the biological objects within an anatomically defined reference space; and local probes such as the nucleator, rotator, and point-sampled intersects that are placed with respect to sampled object of interest. The biological objects of interest generally include cells, fibers, blood vessels, and other features that can be found in a tissue. In practice, trained technicians recognize and indicate the intersections between each probe and the biological objects using a software tool, and the software tool calculates sample parameters for the desired first-order (number, length, surface area, volume) and second-order (variation, spatial distribution) parameters.
Computerization and automation of these processes would be a significant advance toward fully automated applications of design-based stereology for biological tissue analysis.